Settings in School:
Extracurricular Activities

Discretionary behavior in school can be regarded as an extension of the settings/treatments dichotomy to another phase of the life cycle. In this case, as Spaeth (1976) has suggested, youngsters are participating actively in choosing settings in which to place themselves and in the self-administration of "treatments." At least two studies have found a relationship between educational attainment (years of school completed) and participation in extracurricular activities in high school independent of parental SES, academic ability, and academic performance (Spady 1970; Otto 1975). Extracurricular activity has also been suggested as a mechanism by which parental SES is transmitted to offspring (Otto 1975). Otto has postulated that extracurricular activity provides socialization for attitudes and skills that "pay off" later in life.

A rather different perspective has been offered by Coleman in The Adolescent Society (1961). Coleman concentrates on the types of activities in which students are engaged (rather than on the level

of participation), and on the degree to which activities are congruent with high levels of academic achievement and scholarship. Our own analysis will lean more toward the Coleman type of research question. Are there sibsize differences in the types of activities in which young people are engaged after controlling for major family background characteristics? Are young people from small families, including only children, more likely to engage in extracurricular activities that are intellectually and culturally stimulating, in contrast to community-oriented activities, vocationally oriented activities, or sports? In considering the results we will present, the reader should bear in mind that extracurricular activities—especially school activities—are not always perfect indicators of students' principal interests and diversions. Some activities require particular talents and cannot be enjoyed passively, and some may be selected as a change of pace from the student's usual activities, or as an experiment. However, as will be seen, our analysis attempts to deal with this problem.

We will concentrate our analysis on seniors in the High School and Beyond data. Students were asked the questions in figure 7.2. Although it is possible to distinguish between students who had no extracurricular activities during the past school year and those who had one or more such activity, it is not possible to count activities because, in the initial questions, items were grouped (for example, types of sports were grouped, as were activities like debating or drama, chorus or dance, and so on). We thus turned our attention to the types of activities in which students were engaged according to sibsize, rather than to the number of activities.

As a beginning, students could be grouped into those who had no activity, only sports, only nonsports, and both sports and nonsports. For boys and girls, the percentage distributions in these categories are shown in table 7.7. Clearly, few seniors have no activity. Most boys are engaged in sports, or sports and another activity, and girls are engaged modally in a nonsport activity.

The next question was whether the activities of students checking more than one nonsport category formed a pattern. For example, we believed that the activities of dance, band and orchestra, and drama would go together; and that student government, service on school newspapers and magazines, and membership in honor clubs would be cognate. We also saw a congruence between church activi-

Figure 7.2.
Questions Asked of Seniors Concerning Extracurricular Activities
(High School and Beyond).

ties and youth organizations such as Scouts and the "Y." A factor analysis showed that we could combine students engaged in sports and nonsports with nonsports only.^[2]

The analysis showed that we could divide the various nonsport activities into five factors: (1) "Intellectual," (2) "Artistic and Cultural," (3) "Community," (4) "Hobbies," and (5) "Vocational." These factors were then used to assign students to one of the five groups. Students with one nonsport activity were assigned to the relevant group, students with more than one such activity were assigned to the group in which they had the most activities. And if number of activities in all groups was equal, then the student was assigned to the group with which any given activity had the highest correlation. The final distribution is shown in table 7.8.

Among those who have activities (table 7.8), the single most important type of nonsport pursuit for both boys and girls is some form of community involvement—church, youth groups, and so

forth. After community activities, boys and girls divide quite markedly. Boys are more likely to be engaged either in intellectual activities (school newspapers, student government, yearbook, etc.) or in hobby clubs. Girls are more likely to be involved in artistic and cultural activities, or in vocational pursuits. There is a particularly sharp gender discrepancy with regard to hobby clubs and artistic and cultural pursuits—the one almost exclusively a male activity, the other primarily a female activity. It is also true that very few girls are engaged solely in sports, whereas this is true for 11 percent of the boys.

If we assume that the pursuit of "intellectual" activities (and intellectual activities plus sports) provides students with training and experience that will help to further their academic careers, are there sibsize differences between those who engage in such activities versus those who engage in sports only, community only, or community and sports; vocational only, or vocational and sports; or no activity at all? Turning first to boys, the top tier of table 7.9 shows the results of four multiple classification analyses (MCAs). The dependent variable in each case is a dichotomy—" 1 " for intellectual activities, and "0" for only sports, or for community, vocational, or no activity, respectively. The proportions shown have been adjusted for the parents' education, the father's occupation, and whether the family is intact. We see that, in general, boys from small- and medium-size families are more likely to engage in intellectual activities (versus any of the other activities) than are those from large families (sibsizes five and over). Relative to community and vocational activities, only children are particularly likely to engage in intellectual pursuits. The findings are similar if we combine artistic/cultural activities with intellectual activities and redo the MCAs as in the second tier of table 7.9. Boys from small- and medium-size families are also more likely to engage in intellectual (and artistic) activities than no activities at all. However, in this case, only children are slightly less participatory than children from two-child families.

As for girls, since artistic and cultural activities are modal, we have in table 7.10 performed the same analysis as for boys (table 7.9) using Artistic (which includes cultural) in the top tier instead of Intellectual, and combining both Intellectual and Artistic in the second tier. As between artistic and community activities, only

children are clearly more likely to engage in artistic pursuits, whereas there is no difference among the other family sizes. The same pattern appears if we include intellectual activities in the dependent variable. Interestingly, however, only girls are slightly more likely to engage in no activities (than artistic or artistic/intellectual activities) compared with those from families of two to four children. In this respect, only children appear somewhat more like children from large families than those from two- to four-child families.

Children from large families are the most likely to have no activity (when this category is compared with artistic and intellectual).

In sum, only children are particularly unlikely to engage in "community" type activities relative to young people from other sibsizes, and those from small families generally are more likely to engage in intellectual and artistic pursuits than are those from large families. Children from large families are more likely to have no

activity at all than an intellectual or artistic one, and only children are very slightly more likely to have no activity (compared to an intellectual and artistic one) than those from two- to four-child families. Except for this last-mentioned anomaly among only children, it thus appears that coming from a small family versus a large one is associated with extracurricular activities that are congruent with and facilitative of academic and developmental skills. By contrast, those from large families are more likely to engage in sports only, in church activities, youth groups and other community efforts, in vocational activities (boys only), and in no activity at all.

Turning to whether students participate (or do not participate) at all in extracurricular activities, are there major sibsize differences in this behavior? Theoretically, we expect that school grades and type of school program will be major determinants of participation since both schools and parents tend to limit involvement when students have low grades, and schools that are heavily oriented toward vocational and general programs may have limited opportunities for extracurricular activities. It is also true that youngsters from farm families (although often in vocational and general tracks) tend to have uniquely high levels of extracurricular participation because of their involvement in church, community, and farm-related vocational and hobby activities. Those from farm backgrounds also come from larger families.

Accordingly, we limited our multiple classification analysis to senior boys and girls from nonfarm families, and included as predictors high school program, grades, parents' education, father's occupation, whether the family is intact, and sibsize. In addition, we introduced a control for ability as measured by the age-standardized vocabulary test. No major sibsize differences in overall participation for either boys or girls were evident (results not shown here). The principal determinants of participation/nonparticipation are grades and high school program. The major program difference is between academic (higher participation) and other programs (all other variables in the model equal), and there is marked variability in participation by grade performance. The relative importance of program (other variables controlled) is slightly greater than the relative importance of grades. Given controls for grades and program, parents' education is not salient, nor is family intactness.